Overview

Dataset statistics

Number of variables15
Number of observations12500
Missing cells11571
Missing cells (%)6.2%
Duplicate rows147
Duplicate rows (%)1.2%
Total size in memory1.4 MiB
Average record size in memory120.0 B

Variable types

NUM11
CAT4

Reproduction

Analysis started2020-07-12 19:23:04.073872
Analysis finished2020-07-12 19:23:26.867265
Duration22.79 seconds
Versionpandas-profiling v2.8.0
Command linepandas_profiling --config_file config.yaml [YOUR_FILE.csv]
Download configurationconfig.yaml

Warnings

Dataset has 147 (1.2%) duplicate rows Duplicates
quarter has a high cardinality: 100 distinct values High cardinality
city has a high cardinality: 346 distinct values High cardinality
heating_type has a high cardinality: 54 distinct values High cardinality
latitude is highly correlated with lambert_poistion_yHigh correlation
lambert_poistion_y is highly correlated with latitudeHigh correlation
longitude is highly correlated with lambert_poistion_xHigh correlation
lambert_poistion_x is highly correlated with longitudeHigh correlation
construction_year has 2610 (20.9%) missing values Missing
heating_type has 913 (7.3%) missing values Missing
number_of_bedrooms has 7722 (61.8%) missing values Missing

Variables

living_space
Real number (ℝ≥0)

Distinct count3428
Unique (%)27.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean85.66294079999999
Minimum13.2
Maximum326.4
Zeros0
Zeros (%)0.0%
Memory size97.7 KiB

Quantile statistics

Minimum13.2
5-th percentile40.8
Q162.4
median79.2
Q3100.8
95-th percentile152.7048
Maximum326.4
Range313.2
Interquartile range (IQR)38.4

Descriptive statistics

Standard deviation35.87666723
Coefficient of variation (CV)0.4188119961
Kurtosis4.229907393
Mean85.6629408
Median Absolute Deviation (MAD)18.768
Skewness1.540084489
Sum1070786.76
Variance1287.135252
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
722241.8%
 
601941.6%
 
781871.5%
 
661771.4%
 
961591.3%
 
841561.2%
 
901471.2%
 
541431.1%
 
74.41331.1%
 
62.41281.0%
 
Other values (3418)1085286.8%
 
ValueCountFrequency (%) 
13.21< 0.1%
 
14.41< 0.1%
 
15.6121< 0.1%
 
16.83< 0.1%
 
16.9681< 0.1%
 
ValueCountFrequency (%) 
326.41< 0.1%
 
320.41< 0.1%
 
3182< 0.1%
 
310.1761< 0.1%
 
3001< 0.1%
 

rooms
Real number (ℝ≥0)

Distinct count18
Unique (%)0.1%
Missing6
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean2.997702897390748
Minimum1.5
Maximum9.0
Zeros0
Zeros (%)0.0%
Memory size97.7 KiB

Quantile statistics

Minimum1.5
5-th percentile1.5
Q12.5
median3
Q33.5
95-th percentile4.5
Maximum9
Range7.5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9339657431
Coefficient of variation (CV)0.3115604765
Kurtosis1.702485948
Mean2.997702897
Median Absolute Deviation (MAD)0.5
Skewness0.7435259188
Sum37453.3
Variance0.8722920094
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
2.5446035.7%
 
3.5368529.5%
 
1.5139811.2%
 
4.59777.8%
 
39477.6%
 
23272.6%
 
43132.5%
 
5.51861.5%
 
51030.8%
 
6.5440.4%
 
Other values (8)540.4%
 
ValueCountFrequency (%) 
1.5139811.2%
 
23272.6%
 
2.5446035.7%
 
2.770.1%
 
39477.6%
 
ValueCountFrequency (%) 
92< 0.1%
 
8.54< 0.1%
 
84< 0.1%
 
7.5100.1%
 
76< 0.1%
 

cold_rent
Real number (ℝ≥0)

Distinct count3473
Unique (%)27.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1043.16407616
Minimum159.6
Maximum4788.0
Zeros0
Zeros (%)0.0%
Memory size97.7 KiB

Quantile statistics

Minimum159.6
5-th percentile438
Q1658.8
median883.974
Q31267.5
95-th percentile2162.232
Maximum4788
Range4628.4
Interquartile range (IQR)608.7

Descriptive statistics

Standard deviation580.8369474
Coefficient of variation (CV)0.5568030578
Kurtosis5.61917215
Mean1043.164076
Median Absolute Deviation (MAD)282.156
Skewness1.947609099
Sum13039550.95
Variance337371.5595
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
7201641.3%
 
6601601.3%
 
7801481.2%
 
6001451.2%
 
9001451.2%
 
8401291.0%
 
10201281.0%
 
14401221.0%
 
9601211.0%
 
11401040.8%
 
Other values (3463)1113489.1%
 
ValueCountFrequency (%) 
159.61< 0.1%
 
193.2962< 0.1%
 
194.71< 0.1%
 
199.2361< 0.1%
 
202.7641< 0.1%
 
ValueCountFrequency (%) 
47882< 0.1%
 
47401< 0.1%
 
46801< 0.1%
 
46681< 0.1%
 
4654.81< 0.1%
 

construction_year
Real number (ℝ≥0)

MISSING

Distinct count156
Unique (%)1.6%
Missing2610
Missing (%)20.9%
Infinite0
Infinite (%)0.0%
Mean1975.2360970677453
Minimum1622.0
Maximum2023.0
Zeros0
Zeros (%)0.0%
Memory size97.7 KiB

Quantile statistics

Minimum1622
5-th percentile1905
Q11958
median1974
Q32010
95-th percentile2022
Maximum2023
Range401
Interquartile range (IQR)52

Descriptive statistics

Standard deviation36.95557882
Coefficient of variation (CV)0.0187094489
Kurtosis2.987460442
Mean1975.236097
Median Absolute Deviation (MAD)26
Skewness-0.8917614611
Sum19535085
Variance1365.714806
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
20223953.2%
 
20203492.8%
 
20213202.6%
 
19042942.4%
 
20192421.9%
 
19642321.9%
 
20182111.7%
 
19592061.6%
 
20231981.6%
 
19601791.4%
 
Other values (146)726458.1%
 
(Missing)261020.9%
 
ValueCountFrequency (%) 
16221< 0.1%
 
16481< 0.1%
 
16623< 0.1%
 
16681< 0.1%
 
17241< 0.1%
 
ValueCountFrequency (%) 
20231981.6%
 
20223953.2%
 
20213202.6%
 
20203492.8%
 
20192421.9%
 

quarter
Categorical

HIGH CARDINALITY

Distinct count100
Unique (%)0.8%
Missing0
Missing (%)0.0%
Memory size97.7 KiB
Winterhude
 
642
Rahlstedt
 
529
Barmbek-Nord
 
403
Wandsbek
 
380
Eimsbüttel
 
358
Other values (95)
10188
ValueCountFrequency (%) 
Winterhude6425.1%
 
Rahlstedt5294.2%
 
Barmbek-Nord4033.2%
 
Wandsbek3803.0%
 
Eimsbüttel3582.9%
 
Barmbek-Süd3242.6%
 
Harburg3222.6%
 
Langenhorn3202.6%
 
Eppendorf2992.4%
 
Niendorf2892.3%
 
Other values (90)863469.1%
 

Length

Max length20
Median length9
Mean length9.6124
Min length4

lambert_poistion_x
Real number (ℝ)

HIGH CORRELATION

Distinct count7479
Unique (%)60.2%
Missing80
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean565.6875201288245
Minimum-17044.0
Maximum19121.0
Zeros2
Zeros (%)< 0.1%
Memory size97.7 KiB

Quantile statistics

Minimum-17044
5-th percentile-9071.6
Q1-2851
median413
Q33975
95-th percentile10800
Maximum19121
Range36165
Interquartile range (IQR)6826

Descriptive statistics

Standard deviation5827.887744
Coefficient of variation (CV)10.3023092
Kurtosis0.3385108086
Mean565.6875201
Median Absolute Deviation (MAD)3391.5
Skewness0.0272276914
Sum7025839
Variance33964275.55
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1032350.3%
 
481290.2%
 
44280.2%
 
10252260.2%
 
-278200.2%
 
1314200.2%
 
-321200.2%
 
1023200.2%
 
13232180.1%
 
13386160.1%
 
Other values (7469)1218897.5%
 
(Missing)800.6%
 
ValueCountFrequency (%) 
-170441< 0.1%
 
-167431< 0.1%
 
-167321< 0.1%
 
-167161< 0.1%
 
-167061< 0.1%
 
ValueCountFrequency (%) 
191211< 0.1%
 
183661< 0.1%
 
183071< 0.1%
 
180991< 0.1%
 
174931< 0.1%
 

lambert_poistion_y
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count7155
Unique (%)57.6%
Missing80
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean2622120.1461352655
Minimum2603521.0
Maximum2637566.0
Zeros0
Zeros (%)0.0%
Memory size97.7 KiB

Quantile statistics

Minimum2603521
5-th percentile2609967.7
Q12620085
median2622925.5
Q32625299.25
95-th percentile2630694.25
Maximum2637566
Range34045
Interquartile range (IQR)5214.25

Descriptive statistics

Standard deviation5687.424428
Coefficient of variation (CV)0.002169017479
Kurtosis0.5514456637
Mean2622120.146
Median Absolute Deviation (MAD)2620.5
Skewness-0.6767508838
Sum3.256673222e+10
Variance32346796.62
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
2619709330.3%
 
2619599290.2%
 
2633517290.2%
 
2628199260.2%
 
2620710240.2%
 
2625135230.2%
 
2619416210.2%
 
2612553200.2%
 
2619187190.2%
 
2631720180.1%
 
Other values (7145)1217897.4%
 
(Missing)800.6%
 
ValueCountFrequency (%) 
26035211< 0.1%
 
26035461< 0.1%
 
26036501< 0.1%
 
26037731< 0.1%
 
26041531< 0.1%
 
ValueCountFrequency (%) 
26375661< 0.1%
 
26375081< 0.1%
 
26374041< 0.1%
 
26373421< 0.1%
 
26373411< 0.1%
 

city
Categorical

HIGH CARDINALITY

Distinct count346
Unique (%)2.8%
Missing0
Missing (%)0.0%
Memory size97.7 KiB
Hamburg
11564
Hamburg, HafenCity
 
57
Hamburg-Winterhude
 
32
Hamburg-Barmbek
 
17
Hamburg-Hamm
 
17
Other values (341)
 
813
ValueCountFrequency (%) 
Hamburg1156492.5%
 
Hamburg, HafenCity570.5%
 
Hamburg-Winterhude320.3%
 
Hamburg-Barmbek170.1%
 
Hamburg-Hamm170.1%
 
HAMBURG150.1%
 
Hamburg-Lokstedt140.1%
 
Neugraben-Fischbek130.1%
 
Hamburg / Harburg120.1%
 
hamburg120.1%
 
Other values (336)7476.0%
 

Length

Max length50
Median length7
Mean length7.74896
Min length1

postcode
Real number (ℝ≥0)

Distinct count134
Unique (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21745.05856
Minimum2103
Maximum27661
Zeros0
Zeros (%)0.0%
Memory size97.7 KiB

Quantile statistics

Minimum2103
5-th percentile20149
Q121073
median22117
Q322399
95-th percentile22761.1
Maximum27661
Range25558
Interquartile range (IQR)1326

Descriptive statistics

Standard deviation886.6528744
Coefficient of variation (CV)0.04077491316
Kurtosis19.84722492
Mean21745.05856
Median Absolute Deviation (MAD)410
Skewness-1.632490996
Sum271813232
Variance786153.3197
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
210733462.8%
 
210752782.2%
 
204572712.2%
 
202512532.0%
 
223032522.0%
 
220412301.8%
 
205352191.8%
 
225292161.7%
 
222992101.7%
 
220832061.6%
 
Other values (124)1001980.2%
 
ValueCountFrequency (%) 
21031< 0.1%
 
111111< 0.1%
 
200851< 0.1%
 
20095190.2%
 
200971371.1%
 
ValueCountFrequency (%) 
276611< 0.1%
 
235641< 0.1%
 
229993< 0.1%
 
228071< 0.1%
 
228011< 0.1%
 

heating_type
Categorical

HIGH CARDINALITY
MISSING

Distinct count54
Unique (%)0.5%
Missing913
Missing (%)7.3%
Memory size97.7 KiB
5
3815
1
3019
7
2915
6
787
10
 
376
Other values (49)
 
675
ValueCountFrequency (%) 
5381530.5%
 
1301924.2%
 
7291523.3%
 
67876.3%
 
103763.0%
 
81811.4%
 
11800.6%
 
4710.6%
 
17570.5%
 
24520.4%
 
Other values (44)2341.9%
 
(Missing)9137.3%
 

Length

Max length7
Median length1
Mean length1.216
Min length1

number_of_bedrooms
Real number (ℝ≥0)

MISSING

Distinct count7
Unique (%)0.1%
Missing7722
Missing (%)61.8%
Infinite0
Infinite (%)0.0%
Mean1.5663457513604018
Minimum0.0
Maximum6.0
Zeros12
Zeros (%)0.1%
Memory size97.7 KiB

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile3
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.7407892861
Coefficient of variation (CV)0.4729411022
Kurtosis1.414323625
Mean1.566345751
Median Absolute Deviation (MAD)0
Skewness1.211701033
Sum7484
Variance0.5487687663
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
1265721.3%
 
2159112.7%
 
34383.5%
 
4700.6%
 
0120.1%
 
590.1%
 
61< 0.1%
 
(Missing)772261.8%
 
ValueCountFrequency (%) 
0120.1%
 
1265721.3%
 
2159112.7%
 
34383.5%
 
4700.6%
 
ValueCountFrequency (%) 
61< 0.1%
 
590.1%
 
4700.6%
 
34383.5%
 
2159112.7%
 

rent_per_square_meter
Real number (ℝ≥0)

Distinct count1627
Unique (%)13.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.55844416
Minimum6.0
Maximum35.496
Zeros0
Zeros (%)0.0%
Memory size97.7 KiB

Quantile statistics

Minimum6
5-th percentile8.328
Q111.592
median14.04
Q316.872
95-th percentile22.3806
Maximum35.496
Range29.496
Interquartile range (IQR)5.28

Descriptive statistics

Standard deviation4.313337516
Coefficient of variation (CV)0.2962773679
Kurtosis1.668225129
Mean14.55844416
Median Absolute Deviation (MAD)2.64
Skewness0.9190030915
Sum181980.552
Variance18.60488052
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
122712.2%
 
13.21701.4%
 
14.41581.3%
 
181421.1%
 
16.81261.0%
 
151241.0%
 
15.61020.8%
 
13.8960.8%
 
10.8900.7%
 
12.6890.7%
 
Other values (1617)1113289.1%
 
ValueCountFrequency (%) 
670.1%
 
6.061< 0.1%
 
6.0842< 0.1%
 
6.0961< 0.1%
 
6.1441< 0.1%
 
ValueCountFrequency (%) 
35.4961< 0.1%
 
35.42< 0.1%
 
35.221< 0.1%
 
35.1961< 0.1%
 
35.0281< 0.1%
 

publish_date
Categorical

Distinct count41
Unique (%)0.3%
Missing0
Missing (%)0.0%
Memory size97.7 KiB
2019-06-30 22:00:00
 
735
2019-01-31 23:00:00
 
605
2019-05-30 22:00:00
 
555
2019-03-28 23:00:00
 
550
2019-04-30 22:00:00
 
537
Other values (36)
9518
ValueCountFrequency (%) 
2019-06-30 22:00:007355.9%
 
2019-01-31 23:00:006054.8%
 
2019-05-30 22:00:005554.4%
 
2019-03-28 23:00:005504.4%
 
2019-04-30 22:00:005374.3%
 
2019-02-28 23:00:005184.1%
 
2018-05-30 22:00:004013.2%
 
2017-01-31 23:00:003783.0%
 
2018-09-30 22:00:003552.8%
 
2018-08-31 22:00:003462.8%
 
Other values (31)752060.2%
 

Length

Max length19
Median length19
Mean length19
Min length19

latitude
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count9830
Unique (%)79.1%
Missing80
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean53.57021930800015
Minimum53.4006907643781
Maximum53.71090018137016
Zeros0
Zeros (%)0.0%
Memory size97.7 KiB

Quantile statistics

Minimum53.40069076
5-th percentile53.45954298
Q153.55168885
median53.57755594
Q353.59919823
95-th percentile53.6483501
Maximum53.71090018
Range0.310209417
Interquartile range (IQR)0.04750937432

Descriptive statistics

Standard deviation0.05181590098
Coefficient of variation (CV)0.0009672519854
Kurtosis0.5508657812
Mean53.57021931
Median Absolute Deviation (MAD)0.02385509915
Skewness-0.6770937638
Sum665342.1238
Variance0.002684887595
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
53.54828795330.3%
 
53.67406329290.2%
 
53.5472869280.2%
 
53.62552647260.2%
 
53.54561824200.2%
 
53.59771557200.2%
 
53.65769505180.1%
 
53.54353368180.1%
 
53.47859491160.1%
 
53.48295341150.1%
 
Other values (9820)1219797.6%
 
(Missing)800.6%
 
ValueCountFrequency (%) 
53.400690761< 0.1%
 
53.400923611< 0.1%
 
53.401875561< 0.1%
 
53.402964131< 0.1%
 
53.406441991< 0.1%
 
ValueCountFrequency (%) 
53.710900181< 0.1%
 
53.710372261< 0.1%
 
53.709421441< 0.1%
 
53.708858261< 0.1%
 
53.708846391< 0.1%
 

longitude
Real number (ℝ≥0)

HIGH CORRELATION

Distinct count9830
Unique (%)79.1%
Missing80
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean10.008663586462754
Minimum9.73918113969377
Maximum10.291816099465922
Zeros0
Zeros (%)0.0%
Memory size97.7 KiB

Quantile statistics

Minimum9.73918114
5-th percentile9.861395543
Q19.956471245
median10.00631999
Q310.06083863
95-th percentile10.16544689
Maximum10.2918161
Range0.5526349598
Interquartile range (IQR)0.1043673825

Descriptive statistics

Standard deviation0.08916361765
Coefficient of variation (CV)0.008908643684
Kurtosis0.3347149986
Mean10.00866359
Median Absolute Deviation (MAD)0.0518878108
Skewness0.02545852981
Sum124307.6017
Variance0.007950150712
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
10.01578518330.3%
 
10.00737819290.2%
 
10.000673280.2%
 
10.15708566260.2%
 
9.995743041200.2%
 
10.02009737200.2%
 
10.01568625180.1%
 
9.995090601180.1%
 
10.20442725160.1%
 
10.20209525150.1%
 
Other values (9820)1219797.6%
 
(Missing)800.6%
 
ValueCountFrequency (%) 
9.739181141< 0.1%
 
9.7437348191< 0.1%
 
9.7439050261< 0.1%
 
9.7441619141< 0.1%
 
9.7443029181< 0.1%
 
ValueCountFrequency (%) 
10.29181611< 0.1%
 
10.280214821< 0.1%
 
10.279256591< 0.1%
 
10.276292331< 0.1%
 
10.267056691< 0.1%
 

Interactions

Correlations

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

Sample

First rows

living_spaceroomscold_rentconstruction_yearquarterlambert_poistion_xlambert_poistion_ycitypostcodeheating_typenumber_of_bedroomsrent_per_square_meterpublish_datelatitudelongitude
0116.44.51453.2001976.0Farmsen-Berne7967.02625150.0Hamburg221596NaN14.9762019-05-30 22:00:0053.59779310.121997
178.03.0819.600NaNWandsbek5628.02623928.0Hamburg220471NaN12.6122019-01-31 23:00:0053.58669110.086159
262.43.5504.000NaNWilstorf-239.02608361.0Hamburg210791NaN9.6962019-01-31 23:00:0053.4449089.996353
398.43.51131.6001982.0Rahlstedt9481.02628105.0Hamburg221451NaN13.8002019-04-30 22:00:0053.62468510.145269
4144.03.52280.000NaNBlankenese-13093.02620974.0Hamburg2258752.018.9962019-03-28 23:00:0053.5596529.799682
597.83.51128.0002021.0Langenhorn369.02631379.0Hamburg224195NaN13.8362019-02-28 23:00:0053.65459010.005658
660.02.5660.0001964.0Neugraben-Fischbek-9224.02612187.0Hamburg2114761.013.2002019-01-31 23:00:0053.4796859.859130
778.02.5573.7681970.0Marmstorf-2662.02607988.0Hamburg210777NaN8.8322019-06-30 22:00:0053.4415039.959381
861.22.5807.600NaNBarmbek-Nord3091.02625603.0Hamburg223071NaN15.8402019-04-30 22:00:0053.60197010.047336
960.02.5660.0001964.0Neugraben-Fischbek-9224.02612187.0Hamburg2114761.013.2002019-01-31 23:00:0053.4796859.859130

Last rows

living_spaceroomscold_rentconstruction_yearquarterlambert_poistion_xlambert_poistion_ycitypostcodeheating_typenumber_of_bedroomsrent_per_square_meterpublish_datelatitudelongitude
12490256.7048.02916.0001916.0Groß Flottbek-7369.02621225.0Hamburg22607NaNNaN13.6322016-05-30 22:00:0053.5620489.887251
1249165.1842.5900.0001934.0Hamm-Süd3812.02619894.0Hamburg205371NaN16.5722016-06-30 22:00:0053.54996110.058309
1249286.4003.5508.2001970.0Marmstorf-2507.02608023.0Hamburg210777NaN7.0562016-04-30 22:00:0053.4418239.961746
1249374.4002.5912.0001989.0Wellingsbüttel5623.02630277.0Hamburg223915NaN14.7122016-08-31 22:00:0053.64452310.086195
1249459.6402.5399.5881957.0Heimfeld-3146.02611160.0Hamburg210755NaN8.0402016-10-30 22:00:0053.4703999.951964
1249578.8403.5684.0001962.0Rahlstedt8515.02625898.0Hamburg221475NaN10.4162016-01-31 23:00:0053.60459810.130409
1249660.0002.5930.0001874.0Barmbek-Süd1937.02622714.0Hamburg22083NaN1.018.6002016-02-29 23:00:0053.57565910.029646
1249792.9402.5606.000NaNSt. Pauli-2575.02619807.0Hamburg203591NaN7.8242016-10-30 22:00:0053.5491759.960613
1249869.5402.5748.2001939.0Winterhude1231.02624265.0Hamburg2230371.012.9122016-03-29 23:00:0053.58978910.018847
1249973.2003.0518.5321958.0Heimfeld-2245.02610261.0Hamburg210755NaN8.4962016-06-30 22:00:0053.4622139.965728

Duplicate rows

Most frequent

living_spaceroomscold_rentconstruction_yearquarterlambert_poistion_xlambert_poistion_ycitypostcodeheating_typenumber_of_bedroomsrent_per_square_meterpublish_datelatitudelongitudecount
459.3523.0742.8001961.0Ohlsdorf2088.02626963.0Hamburg2233752.015.0242017-02-28 23:00:0053.61436310.0319853
051.3722.5328.7642022.0Othmarschen-6435.02620790.0Hamburg2276371.07.6802018-07-30 22:00:0053.5580979.9015502
153.6401.51421.4602022.0HafenCity-321.02619187.0Hamburg, HafenCity2045771.031.8002019-03-28 23:00:0053.5435349.9950912
254.0001.5745.2001955.0Horn5265.02620184.0Hamburg2211151.016.5602019-02-28 23:00:0053.55259010.0805402
355.2001.5972.0002020.0Hoheluft-West-1910.02623459.0Hamburg2025351.021.1322017-08-31 22:00:0053.5824459.9707632
560.0002.5660.0001964.0Neugraben-Fischbek-9224.02612187.0Hamburg2114761.013.2002019-01-31 23:00:0053.4796859.8591302
660.0002.5750.0001878.0Borgfelde1896.02620652.0Hamburg20535191.015.0002019-05-30 22:00:0053.55687610.0290062
765.4002.5552.0001897.0Wilhelmsburg1385.02615541.0Hamburg2110951.010.1282018-09-30 22:00:0053.51031810.0211662
866.0002.5660.0001998.0Wandsbek5253.02623306.0Hamburg2204151.012.0002019-05-30 22:00:0053.58102910.0804082
966.0002.5890.4002019.0Niendorf-3971.02628213.0Hamburg2245951.016.1882017-03-28 23:00:0053.6257389.9391542